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Providence · 3 hours ago

Associate Bioinformatics Scientist

Seattle, WA, United States

Full-time

Onsite

Entry, Mid Level

$39.45/hr - $61.24/hr

2+ years exp

Providence is a not-for-profit health care system in the greater Puget Sound area, seeking an Associate Bioinformatics Scientist. The role involves providing bioinformatics support for the analysis of high throughput molecular and genomic data, and developing methods for data integration and interpretation in immuno-oncology projects.

Hospital & Health Care

Responsibilities

Providing comprehensive bioinformatics support for the analysis and interpretation of advanced, high throughput molecular, genomic and clinical data types including gene expression, imaging, electronic medical records, etc

Develop and apply bioinformatics methods and software tools for analysis and integration with clinical information

Perform tasks to reduce and consolidate data output to help interpret and prioritize findings for numerous immuno-oncology focused projects

Qualification

BioinformaticsNext Generation SequencingComputational BiologyClinical InformaticsData ManagementData MiningStatistical MethodsHTML/CSSJavaScriptSQLWeb FrameworksTeam CollaborationIndependent Work

Required

Bachelor's Degree in Bioinformatics, Computational Biology, Computer Science, Engineering, or Biology

Master's Degree in Bioinformatics, Computational Biology, Computer Science, Engineering, or Biology --or-- 5 years of equivalent professional experience in lieu of Master's Degree

2 years of experience related to bioinformatics work in a clinical laboratory or experience in academia, biotechnology, or other healthcare field (preferably involving next generation sequence data analysis)

Significant computational experience

First-hand experience in clinical informatics and/or NGS analysis and methods as well as the computing infrastructure and data management methods

First-hand multi-parametric data mining experience on expression, copy number and profiling datasets for target identification and biomarker discovery. For example, multivariate analysis; dimensionality reduction methods; parametric and non-parametric statistical methods; Bayesian statistics; pattern recognition or classification methods

First-hand experience at integrating publicly or commercially available genetic, genomic, and interaction datasets with novel experimental data to identify testable hypotheses

Proven experience and success in a team-oriented environment

Proven success in independent effort and delivering high quality data with biological relevance in a team environment

Preferred

Experience with the following: Clinical data analysis/Large dataset analysis in R

Analyzing next generation sequencing data (DNA-seq, RNA-seq, etc.)

Commonly used database and bioinformatics tools for NGS data analysis (e.g.) bedtools, SAMtools, IGV, ANNOVAR, Bowtie, GATK, ChimeraScan, UCSC Genome Browser, Galaxy, SoftGenetics, CLC bio, TopHat, etc.)

Web framework (e.g. Django, Sinatra, Rails or others)

HTML/CSS, Javascript and SQL on NoSQL databases